Literature DB >> 15809098

Comparison of STFT and wavelet transform methods in determining epileptic seizure activity in EEG signals for real-time application.

M Kemal Kiymik1, Inan Güler, Alper Dizibüyük, Mehmet Akin.   

Abstract

Electroencephalography (EEG) is widely used in clinical settings to investigate neuropathology. Since EEG signals contain a wealth of information about brain functions, there are many approaches to analyzing EEG signals with spectral techniques. In this study, the short-time Fourier transform (STFT) and wavelet transform (WT) were applied to EEG signals obtained from a normal child and from a child having an epileptic seizure. For this purpose, we developed a program using Labview software. Labview is an application development environment that uses a graphical language G, usable with an online applicable National Instruments data acquisition card. In order to obtain clinically interpretable results, frequency band activities of delta, theta, alpha and beta signals were mapped onto frequency-time axes using the STFT, and 3D WT representations were obtained using the continuous wavelet transform (CWT). Both results were compared, and it was determined that the STFT was more applicable for real-time processing of EEG signals, due to its short process time. However, the CWT still had good resolution and performance high enough for use in clinical and research settings.

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Year:  2005        PMID: 15809098     DOI: 10.1016/j.compbiomed.2004.05.001

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN: 0010-4825            Impact factor:   4.589


  23 in total

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Journal:  J Med Syst       Date:  2010-04-07       Impact factor: 4.460

8.  Software development for the analysis of heartbeat sounds with LabVIEW in diagnosis of cardiovascular disease.

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9.  Integration of 24 Feature Types to Accurately Detect and Predict Seizures Using Scalp EEG Signals.

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10.  Variability analysis of epileptic EEG using the maximal overlap discrete wavelet transform.

Authors:  Jack L Follis; Dejian Lai
Journal:  Health Inf Sci Syst       Date:  2020-09-15
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